Smart Labeling

Machine learning assistance to accelerate ROI on your AI initiatives

Our Smart Labeling capabilities have built-in Machine Learning assistance to save customers time, effort and money - delivering hight-quality training data and accelerating the ROI and your AI initiatives.

Ensuring you have enough labeled data to adequately train your models is no easy feat. Each model may need hundreds of thousands, if not millions of rows of labeled training data from which to lean. Collecting and annotating that amount of high-quality data consumes a lot of time and resources - especially if you’re relying on the power of human annotations alone.

That’s why our industry leading data annotation platform has Smart Labeling. This suite of innovative capabilities uses Machine Learning assistance in the data annotation process to automate and improve productivity, quality, and delivery of your data collection and data annotation projects.

Appen Smart Labeling Focuses
on Three Specific Areas

Machine Learning can drive quality, cost and time saving in the data annotation process:

Pre-Labeling

Machine Learning provides an initial 'best guess' hypothesis before contributors start the task. With human contributors reviewing pre-processed annotations instead of starting a judgment from scratch, the time needed to annotate data drastically reduces.

Speed Labeling

Machine Learning provides for in-tool efficiency, quality and accuracy improving ergonomic conditions while contributors work. This reduces cognitive strain and allows contributors to work faster and more comfortable, increasing throughput of their annotations.

Smart Validators

Our Machine Learning models verify human judgments before they are finalized. This ensures you are only paying for quality judgements, eliminating the need for peer reviews and the risk you’re paying for judgements that don’t fit your requirements.

Customers Running World-Class AI

Smart Labeling Capabilities
our Customers Enjoy

Pre-Labeling for Autonomous Vehicle Image Pixel Labeling

Images are automatically applied with Pixel Labeled classes based on the ontologies you choose. They are then reviewed by a contributor to ensure the annotations are correct and to your specifications. Our statistically significant A/B tests show Pre-Labeling PLSS can improve contributor productivity by 91.5% without quality compromise.

Video Annotation with Speed Labeling

Videos are split into frame-by-frame sequences. Contributors label each object in the first frame, then Speed Labeling tracks and predicts object locations in subsequent frames for the remaining frames. Contributors can then supervise and correct as needed. This results in annotation speeds up to 100x faster than using human annotations alone.

Image Transcription with Speed Labeling

Contributors box text in an image and then OCR assistance predicts transcribed text for each box. Contributors can adjust text as needed. Output includes whether the transcription was provided by the model or by the contributor. Speed Labeling increases efficiency by 33%.

Text Utterance Collection with Smart Validators

Utterances are checked against three validators (duplicate detection, coherence detection and language detection) before being eligible for submission. This tool is commonly used to train chatbots, resulting in up to a 35% reduction in error rates using real time models.

Secure Data Access

Data security requirements are met for customers working with personally identifiable information (PII), protected health information (PHI), and other sophisticated compliance needs.

We have enterprise level security options to suit your sensitive data needs,

Secure Crowd

We offer a suite of secure service offerings with flexible options to ensure data security via secure facilities, secure remote workers, and onsite services to meet specific business needs.

We have enterprise level security options to suit your sensitive data needs,